Unravelling transcriptomic complexity in breast cancer through modulation of DARPP-32 expression and signalling pathways

DARPP-32 is a key regulator of protein-phosphatase-1 (PP-1) and protein kinase A (PKA), with its function dependent upon its phosphorylation state. We previously identified DKK1 and GRB7 as genes with linked expression using Artificial Neural Network (ANN) analysis; here, we determine protein expression in a large cohort of early-stage breast cancer patients. Low levels of DARPP-32 Threonine-34 phosphorylation and DKK1 expression were significantly associated with poor patient prognosis, while low levels of GRB7 expression were linked to better survival outcomes. To gain insight into mechanisms underlying these associations, we analysed the transcriptome of T47D breast cancer cells following DARPP-32 knockdown. We identified 202 differentially expressed transcripts and observed that some overlapped with genes implicated in the ANN analysis, including PTK7, TRAF5, and KLK6, amongst others. Furthermore, we found that treatment of DARPP-32 knockdown cells with 17β-estradiol or PKA inhibitor fragment (6–22) amide led to the differential expression of 193 and 181 transcripts respectively. These results underscore the importance of DARPP-32, a central molecular switch, and its downstream targets, DKK1 and GRB7 in breast cancer. The discovery of common genes identified by a combined patient/cell line transcriptomic approach provides insights into the molecular mechanisms underlying differential breast cancer prognosis and highlights potential targets for therapeutic intervention.


RNA-Seq assessment
Trim Galore version 0.6.7 was used to remove the first 13 base pairs of Illumina standard adaptors (AGA TCG GAA GAG C), perform quality trimming (Phred score cutoff 20), and allowed subsequent FastQC analysis.Kallisto was used to quantify the abundance of transcripts from RNA-Seq data using pseudoalignment 41 .The human reference genome was GENCODE GRCh38 version 36 for transcript identification and quantification.The differential expression of transcripts was determined using DESeq2 (1.36.0) in the statistical environment RStudio, relying on input from Kallisto using Tximport.RStudio version 2022.07.1 + 554 running R version 4.2.0, with Bioconductor version 3.15 were used for assessments 42 .The list of transcripts was subject to a multiple test adjustment ranked by a P < 0.05 and a greater than two-fold change.Gene enrichment analysis was performed using Qiagen Ingenuity Pathway Analysis (IPA) version 76765844.

Nottingham patient cohort and immunohistochemistry
Patients with early-stage invasive breast cancer were treated at Nottingham University Hospitals between 1998 and 2006 and underwent wither breast conserving surgery or mastectomy, which was decided by disease characteristics or patient choice, followed by radiotherapy if indicated.Nottingham Prognostic Index (NPI), ER and menopausal status determined if patients received systemic adjuvant treatment.Patients with an NPI score less than 3.4 did not receive adjuvant treatment, and patients with an NPI score of 3.4 and above were candidates for CMF combination chemotherapy (cyclophosphamide, methotrexate and 5-fluorouracil) if they were ERnegative or pre-menopausal; and hormonal therapy if they were ER-positive.No patients received trastuzumab.
Immunohistochemistry was performed on tissue microarrays that were comprised of single 0.6 mm cores taken from representative tumour areas selected by a specialist breast cancer histopathologist from haematoxylin and eosin stained sections.Tissue microarray sections (4 µm) were initially deparaffinised and rehydrated in sequentially in xylene, ethanol and water prior to antigen retrieval in 0.01 mol L −1 sodium citrate buffer (pH 6.0), with tissue heated in a microwave for 10 min at 750W, and then 10 min at 450W.Staining was performed using a Novolink Polymer Detection kit (Leica) using the manufacturer's instructions.Primary antibodies were incubated on tissue for one hour at room temperature (anti-DKK1 1:1000 (Thermo Fisher Scientific, MA5-32229); anti-GRB7 1:500 (Abcam, ab183737); anti-DARPP-32 phosphorylated Thr-34 1:500 (Abcam ab254063)).
Following staining, tissue was dehydrated in ethanol and fixed in xylene prior to mounting using DPX.For each staining run, control breast composite sections comprised of grade 1 and 2 tumours were utilised.Slides were scanned at 20× magnification using a Nanozoomer Digital Pathology Scanner (Hamamatsu Photonics).An immunohistochemical H-score technique was used to assess cytoplasmic staining, whereby the percentage area of tumour staining was classified as 0 to 3, representing, none, weak, intermediate and strong intensity staining.Nuclear staining was scored as the percentage of tumour cells demonstrating any level of staining.Greater than 30% of cores were scored by an independent assessor, with single measure intraclass correlation coefficient values above 0.7 indicating good concordance between scorers.

Statistics
Statistical analysis was performed using IBM SPSS Statistics (version 28).Cases were stratified based on breast cancer specific survival using X-Tile software and breast cancer specific survival 43 .All differences were deemed statistically significant at the level of P ≤ 0.05.The Pearson χ2 test of association was used to determine the relationship between categorised protein expression and clinicopathological variables.Survival curves were plotted according to the Kaplan-Meier method with significance determined using the log-rank test.

DKK1 expression in early-stage breast cancer patients
DKK1 protein expression was determined in a cohort of early-stage breast cancer patients.Tissue from 1036 patients were available for assessment, the median H-score for cytoplasmic expression of DKK1 was 110 (ranging between 10 and 260), the median H-score for nuclear DKK1 expression was 25 (ranging between 0 and 100); representative tissue staining is shown in Fig. 1.

GRB7 expression in early-stage breast cancer patients
GRB7 expression was determined in a cohort of early-stage breast cancer patients.Tissue from 1408 patients were assessed where the median H-score for cytoplasmic expression of GRB7 was 0 (ranging from 0 to 290), the median H-score for nuclear GRB7 expression was 0 (ranging between 0 and 90); representative tissue staining is shown in Fig. 1.A small number of cores did not have a nuclear score assigned due to difficulties in determination.Low nuclear and cytoplasmic expression of GRB7 was significantly associated with good prognosis of breast cancer patients (P = 0.012, P = 0.003 respectively) (Fig. 2).Multivariate analysis was performed using Cox's proportional hazard method, and included tumour size, tumour grade, tumour stage, NPI, ER status, PgR status, HER2 status and vascular invasion, both nuclear GRB7 and cytoplasmic GRB7 expression was not associated with patient survival in these models (HR = 0.953, 95% CI = 0.617-1.472,P = 0.828, and HR = 1.090.95% CI = 0.656-1.809,P = 0.740).

DARPP-32 knockdown in T47D breast cancer cell line
We sought to identify transcriptomic changes that follow changes in DARPP-32 expression, in the presence and absence of oestrogen and a PKA inhibitor.T47D breast cancer cells were treated with either human DARPP-32 siRNA oligo duplex or negative control siRNA to knockdown DARPP-32 expression.DARPP-32 expression was effectively reduced using siRNA knockdown; protein expression of DARPP-32 was reduced by over 95% determined using Western blotting (Fig. 3B), and over 60% at the mRNA level, using real-time PCR (Fig. 3C); negative control siRNA did not cause a reduction in DARPP-32 expression.
DARPP-32 knockdown cells were also subject to stimulation with E2 or a PKA inhibitor.The PKA inhibitor caused a dose dependent decrease in PKA activity determined by ELISA (Fig. 3D).For RNA-Seq, cells were treated with 3 µM PKA inhibitor for 24 h, which resulted in a 60% reduction in PKA activity, and a 60% reduction in DARPP-32 Thr-34 phosphorylation, which was also determined by ELISA (Fig. 3E).

RNA-Seq of DARPP-32 knockdown T47D breast cancer cells
When DARPP-32 expression was knocked down in T47D breast cancer cells, 202 differentially expressed transcripts were identified (listed in Supplementary file 1).Following stimulation with E2, 193 differentially expressed transcripts were identified between DARPP-32 knockdown cell treated with E2 versus control cell treated with E2 (listed in Supplementary file 1).When DARPP-32 knockdown T47D cells were treated with a PKA inhibitor and compared with control cells treated with a PKA inhibitor, 181 differentially expressed transcripts were identified (listed in Supplementary file 1).The lists of differentially expressed transcripts were explored for common transcripts between those identified following DARPP-32 knockdown, and then in the presence of E2 or a PKA inhibitor (Table 3A).PUF60, and SART3, were identified in DARPP-32 knockdown cells and when DARPP-32 knockdown cells were treated with E2.FIGNL1, TBK1, TSEN34, UBE3A, and ZCCHC7 were identified in DARPP-32 knockdown cells, and when DARPP-32 knockdown cells were treated with a PKA inhibitor.BCLAF1, CAST, CELF1, CTNBB1, KIAA1217 and SMARCE1 were common to DARPP-32 knockdown cells treated with E2 and a PKA inhibitor.RBM39 and SLC10A3 were common to all three datasets.
Qiagen IPA was used to find enriched canonical pathways, 14 were identified when DARPP-32 expression was knocked down.When DARPP-32 knockdown cells were treated with E2, 105 pathways were significantly altered, and 241 when DARPP-32 knockdown cells were treated with a PKA inhibitor (listed in Supplementary file 2).Expectedly dopamine-DARPP-32 feedback in cAMP signaling was one of the 14 pathways identified when DARPP-32 expression was knocked down; the tight junction pathway was common to all three assessments.Qiagen IPA assessment of upstream regulators identified on transcriptional regulator with predicted activation due to changes to target genes in the DARPP-32 knockdown dataset.Changes to CBFA2T3, CEMIP2, KDM3A, MTF2 and NOTCH4 expression indicated activation of the upstream regulator SOX2.

RNA-Seq assessment and commonalities with Artificial Neural Network analysis of META-BRIC cohort
The significant differentially expressed transcripts identified through RNA-Seq of DARPP-32 knockdown T47D breast cancer cells were compared with those identified as associated with PPP1R1B expression in the META-BRIC patient cohort using ANN analysis to find common genes.Of the 202 transcripts identified using RNA-Seq, seven of those were common to the top 300 genes identified using ANN analyses (Table 3B).All seven of the common genes were identified in gene lists from the ANN of PPP1R1B probes 2 and 3. PTK7, PPFIBP2 and PACSIN2 were identified in the ANN of PPP1R1B probes 2 and 3, whilst TRAF5, KLK6, GAL3ST4 were identified within the PPP1R1B probe 2 analysis, and LIMCH1 was identified within the PPP1R1B probe 3 analysis.
Common genes were also identified between the expression of PPP1R1B probes and DARPP-32 knockdown cells that were treated with E2 and that were treated with a PKA inhibitor.EHMT2, KCNIP2, GOLGA2, and ADCY1, were identified in the ANN of PPP1R1B probe 1 and when DARPP-32 knockdown cells were treated with E2.GSTCD was identified in the ANN of PPP1R1B probe 2 and when DARPP-32 knockdown cells were treated No common genes were identified in the ANN of PPP1R1B probe 1 when DARPP-32 knockdown cells were treated with a PKA inhibitor.BMPR1B, and MTA1 were identified in the ANN of PPP1R1B probe 2 when DARPP-32 knockdown cells were treated with a PKA inhibitor and ARL6IP4 was identified in the ANN of probe 3.
PAQR6 was identified in the ANN of PPP1R1B probe 1 and probe 2 and when DARPP-32 knockdown cells were treated with E2.No genes were identified that were common to all three PPP1R1B probes between the three datasets.

Conclusion
In a previous study, we established an association between low DARPP-32 expression and poor prognosis of breast cancer patients, particularly those with ER positive tumours 24 .However, the underlying mechanism by which DARPP-32 impacts breast cancer cell behaviour remains unknown.Using an ANN analysis we identified 18 transcripts common to expression of all three available PPP1R1B probes within the top 200 transcripts for each probe, including DKK1 and GRB7.To further investigate this finding, we conducted a large-scale cohort study to determine GRB7 and DKK1 protein expression levels in combination with determining levels of DARPP-32 Thr-34 phosphorylation in the same patient specimens.In this study we utilised the level of DARPP-32 Thr-34 phosphorylation as a proxy for full-length DARPP-32 expression.DARPP-32 Thr-34 can act as a surrogate of full length DARPP-32 phosphorylation as t-DARPP is lacking this residue; unfortunately, DARPP-32 Thr-75 phosphorylation could not be determined with sufficient accuracy to warrant further study.Our results show that low levels of DARPP-32 Thr-34 phosphorylation was significantly associated with poor patient prognosis, which was in direct alignment with our previous findings 24 .Notably, this association remains significant for nuclear DARPP-32 Thr-34 phosphorylation in multivariate survival analysis.Additionally, DARPP-32 Thr-34  www.nature.com/scientificreports/phosphorylation was significantly associated with advanced tumour stage and lymph node involvement.This study provides further validation that DARPP-32 may be a clinically relevant biomarker in breast cancer.DKK1 is a secretory antagonist of the classical Wnt signalling pathway; studies have indicated that dysregulation of the Wnt signalling pathway, induced via the activity of DKK1, is important to cancer cell migration and bone metastasis in lung, breast and prostate cancer [44][45][46] .Contrasting results demonstrate that whilst overexpression of DKK1 is linked with migration and invasion of hepatocellular carcinoma, DKK1 inhibits migration and invasion of colon and breast cancer [47][48][49] .In this study, low expression of DKK1 was significantly associated with adverse breast cancer specific survival.In addition, low levels of DKK1 expression associated with larger tumours, higher tumour grade, and ER and PgR negative tumours.As expected, we observed a weak but statistically significant correlation between DKK1 expression and DARPP-32 Thr-34 phosphorylation.
GRB7 is a 532 amino acid adaptor molecule with a crucial role in the activation of multiple intracellular pathways through transmission of signals from cell membrane receptors.In this study low nuclear and cytoplasmic expression of GRB7 was significantly associated with good prognosis of breast cancer patients.In addition, low levels of GRB7 expression were associated with lower tumour grade, tumour stage, ER and PgR positive tumours and HER2 negative tumours.This is aligned with previous studies that have demonstrated that low GRB7 expression is associated with improved survival of breast cancer patients (n = 638) 50 and GRB7 is included in the 21 gene set of Oncotype DX.As expected, we observed a weak but statistically significant correlation between GRB7 expression and DARPP-32 Thr-34 phosphorylation.An association between PPP1R1B and GRB7 has been previously demonstrated in upper gastrointestinal adenocarcinomas 51 .
Using the ER positive breast cancer cell line, T47D, we sought to identify transcriptomic changes that follow changes in DARPP-32 expression, in the presence and absence of oestrogen and a PKA inhibitor.The actions of E2, or 17β-estradiol, are mediated by ER, and treatment of T47D cells with 10 nM E2, has been shown to increase cellular proliferation with significant changes in the transcriptome, including the expression of important cancer associated genes, such as MYC [52][53][54][55] .PKA inhibition with PKA inhibitor fragment (6-22) amide was used determine transcriptomic changes that occur following reduction of PKA mediated DARPP-32 Thr-34 phosphorylation; however, PKA inhibition would also be expected to alter a wide range of cell signalling effects directly through PKA.PKA inhibitor fragment (6-22) amide is a potent inhibitor of PKA that is derived from the active portion of the heat stable PKA inhibitor protein, PKI.In T47D cells, 24-h 3 µM PKA inhibitor treatment resulted in a 60% inhibition of PKA, and a 60% decrease in DARPP-32 Thr-34 phosphorylation.202 differentially expressed transcripts were identified following knockdown of DARPP-32.Following stimulation with E2, 193 differentially expressed transcripts were identified and 181 following treatment with a PKA inhibitor.Transcripts common to multiple assessments were identified, with PUF60, and SART3 common to DARPP-32 knockdown cells and DARPP-32 knockdown cells treated with E2.FIGNL1, TBK1, TSEN34, UBE3A, and ZCCHC7 were common to DARPP-32 knockdown cells and DARPP-32 knockdown cells treated with a PKA inhibitor.RBM39 and SLC10A3 were common to all three DARPP-32 knockdown RNA-Seq data sets; RBM39 encodes RNA binding motif protein 39 (RBM39), and SLC10A3 encodes solute carrier family 10 member 3.
Transcripts common to multiple assessments included a number of genes linked to breast cancer.Expression of PUF60, a spliceosome component, is associated with overall survival in breast cancer 56 , and SART3 has previously been identified as expressed in a large proportion of breast cancer cell tissue 57 .Serum levels of TBK1, are associated with the clinical outcome of breast cancer patients 58 and ubiquitin protein ligase E3A (UBE3A) has been shown to be overexpressed in breast cancer 59 .RBM39 and SLC10A3 were common to all datasets and have been linked with tumour cell behaviour 60 and high expression associated with adverse survival of hepatocellular cancer patients 61 , respectively.
The transcripts identified through RNA-Seq of DARPP-32 knockdown T47D breast cancer cells were compared with those identified as associated with PPP1R1B expression in the METABRIC patient cohort.Seven genes were identified that were common between lists, with all identified in ANN gene lists from PPP1R1B probe 2 and 3. PTK7, PPFIBP2 and PACSIN2 were identified in the ANN of PPP1R1B probes 2 and 3, TRAF5, KLK6, GAL3ST4 were identified within the PPP1R1B probe 2 analysis, and LIMCH1 was identified within the PPP1R1B probe 3 analysis.Common genes were also identified between the METABRIC ANN and in DARPP-32 knockdown cells treated with E2 and the PKA inhibitor.Of these genes, PTK7, KLK6 and LIMCH1 have interesting links with breast cancer; PTK7 is a catalytically inactive receptor tyrosine kinase in the Wnt signalling pathway, and a PTK7 targeted antibody-drug conjugate has been shown to reduce tumour-initiating cells 62 .Both KLK6 and LIMCH1 expression has been linked to clinical outcome of breast cancer patients 63,64 .
The significant associations observed between DARPP-32 and its downstream targets DKK1 and GRB7 and patient survival, underscore their importance in breast cancer.By using an approach that combines patient and cell line transcriptomics we have identified a number of common genes that provides an insight into the molecular mechanisms underlying differential breast cancer prognosis and highlights potential targets for therapeutic intervention.

Table 1 .
Associations between the cytoplasmic and nuclear expression of DKK1 and GRB7 determined using immunohistochemistry with clinicopathological variables.The P values are resultant from Pearson χ 2 test of association and significant values (P < 0.05) are highlighted in bold.ER is oestrogen receptor and PgR is progesterone receptor.

Table 2 .
Associations between the cytoplasmic and nuclear expression of DARPP-32 Thr-34 phosphorylation determined using immunohistochemistry with clinicopathological variables.The P values are resultant from Pearson χ 2 test of association and significant values (P < 0.05) are highlighted in bold.ER is oestrogen receptor and PgR is progesterone receptor.

Table 3 .
(A) lists differentially expressed transcripts common to multiple analysis groups, where PKAi is PKA inhibition.(B) lists genes common to both RNA-Seq of DARPP-32 knockdown cells and ANN of PPP1R1B probes.